B. The linear correlation coefficient r is ____ Determine the null and alternative hypotheses. H0: ρ ( > or < or = or ≠) ___ H1:ρ ( > or < or = or ≠) ___ The test statistic is ____ C. The P-value is ____ Because the P-value of the linear correlation coefficient is ( greater than/ less or equal to) the significance level, there (is/ is not) sufficient evidence to support the claim that there is a linear correlation between the ages of Best Actresses and Best Actors. Should we expect that there would be a correlation? Yes or No.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
B. The linear
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Determine the null and alternative hypotheses.
H0: ρ ( > or < or = or ≠) ___ H1:ρ ( > or < or = or ≠) ___
- The test statistic is ____
C. The P-value is ____
- Because the P-value of the linear correlation coefficient is ( greater than/ less or equal to) the significance level, there (is/ is not) sufficient evidence to support the claim that there is a linear correlation between the ages of Best Actresses and Best Actors.
- Should we expect that there would be a correlation?
Yes or No.
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